Additive manufacturing has become an important industrial process for the manufacture of custom-made metal parts. EBFFF, also referred to as Electron Beam Additive Manufacturing (EBAM), is a rapid metal deposition process that works efficiently with a variety of weldable alloys. Starting with a 3D model from a CAD program of the part to be built, the EBFFF process builds the part layer by layer on a substrate of metal by introducing metal wire feedstock into a molten pool that is created and sustained using a focused electron beam in a vacuum environment. Operation in a vacuum ensures a clean process environment and eliminates the need for a consumable shield gas.
The EBFFF process has been shown to be a leading candidate for generating large near-net-shaped preforms. It has been demonstrated that significant cost savings can be realised using this process when compared to conventional processes due to the reduction in raw material usage and minimised lead times.
Residual stress and shape distortion are inherent features of additive manufacturing, particularly at high deposition rates which require high heat input to the substrate and previously deposited layers, resulting in large thermal gradients. In most cases, fabricated parts are heat treated after deposition to help relieve stresses. As a result, the presence of high stress leading to premature failure during service is not as much of a concern as are stress and stress-induced distortion during and after deposition. Residual stress and distortion associated with the EBFFF process are currently addressed by frequent stress-relieving steps during the build. However, such steps are cumbersome, time consuming and add to the production cost of objects manufactured using the EBFFF process.
It would be desirable to minimise the stress-relieving steps required during additive manufacturing. It would also be desirable to provide a means of improving the efficiency of additive manufacturing processes, and in particular to better manage the distortion and residual stress associated with additive manufacturing. It would also be desirable to provide a tool for predicting distortion in an additive manufacturing process so that measures can be taken to compensate for that distortion.